• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.13 no.6
• /
• pp.54-63
• /
• 2014

Traffic accident frequency and severity level in Korea are known to be very serious. Especially the number of pedestrian fatalities was much worse and 1.6 time higher than the OECD average. According to the National Police Agency, the flash signals are reported to have many safety benefits as well as travel time reduction, which is opposed to the foreign studies. With this background of expanding the flash signal, this research aims to investigate the overall impact of the flash signal operation on safety, investigating and comparing the accident occurrence on the flash signal and the full signal intersections. For doing this accident prediction models for both flash and full signal intersections were estimated using independent variables (geometric features and traffic volume) and 3-year (2011-2013) accident data collected in Seoul. Considering the rare and random nature of accident occurrence and overdispersion (variance > mean) of the data, the negative binomial regression model was applied. As a result, installing wider crosswalk and increasing the number of pedestrian push buttons seemed to increase the safety of the flash signal intersections. In addition, the result showed that the average accident occurrence at the flash signal intersections was higher than at the full signal-operated intersections, 9% higher with everything else the same.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.2
• /
• pp.1-16
• /
• 2022

The location of the bus stop on urban roads should be installed at a point where it is convenient for users and the impact of bus stops on the traffic flow is minimized. However, the location of the bus stops is determined indiscriminately due to the lack of related research. Therefore, this study developed a traffic accident prediction model and calculated the proper separation distance for the bus stops through an optimization technique. The result of the study indicates that the bus stop can be installed in the form of a mid-block approximately 87 to 166 m away from the intersection in the road section. This result is valid if the number of main road lanes in the road section is 2 to 4 with a level of traffic from 1,000 to 3,000 v/h. In the section with 5 to 6 lanes, it is desirable to install a bus stop close to the intersection by about 42 to 97 m.

• Journal of Korean Society of Transportation
• /
• v.34 no.4
• /
• pp.291-303
• /
• 2016

The number of traffic accidents at intersections has been increased over the past decade, and in 2014, accounted for 44% of the total traffic accidents. In addition, since most of road accident black spots include signalized intersections, the improvement of safety on signalized intersection is top priority for national road safety program in Korea. For the decision of most effective action plan for the safety of signalized intersection, this study conducted meta-analyses to assess the effects of various road safety facilities at signalized intersection on traffic accidents. We selected 19 articles regarding the prediction of traffic accidents at signalized intersection and calculated 34 individual effect sizes on 8 variables included in the articles. The results found that there was a statistically significant negative relationship between the occurrence of traffic accident and the presence of all of road safety facilities except an exclusive left turn bay. It shows that most of the road safety facilities could prevent traffic accidents, and intersection channelization has the most effective on the reduction of traffic accidents followed by left-turn acceleration lane, lightning, crosswalk, exclusive right-turn lane and median barrier.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.39 no.1
• /
• pp.73-80
• /
• 2019

Traffic Safety and efficient Road Traffic Policy of Traffic management came into effect over the certain size of the road like main road. Comparatively, Safety for Living street is deteriorated. Especially, Vehicle are usually priority to the life-zone street, even though Safety for the Passengers are essential to the life-zone street in the residential area. Improvement for the Living street has not been achieved In this study, To suggest Intersection Notifications standard of installation in Living Street, We execute on-site survey in priority to Gwangju Metropolitan City. Furthermore, After We suggest experimental value for the Intersection Notifications' standard of installation Prediction model in the Living street, Intersection Notifications compare & veritfy experimental value to the installation point's value to suggest the standard of installation in the living street. As a result, We can prevent frequent traffic accident in the Living Street. Furthermore, We are judged by installation of intersection Notifications considering stability and convenience to the passengers who are using the living street.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.15 no.1
• /
• pp.1-15
• /
• 2016

This study aims to develop a model by which city bus drivers who are likely to cause an accident can be figured out based on the information about their actual driving records. For this purpose, from the information about the actual driving records of the drivers who have caused an accident and those who have not caused any, significance variables related to traffic accidents are drawn, and the accuracy between models is compared for the classification models developed, applying a discriminant analysis and logistic regression analysis. In addition, the developed models are applied to the data on other drivers' driving records to verify the accuracy of the models. As a result of developing a model for the classification of drivers who are likely to cause an accident, when deceleration ($X_{deceleration}$) and acceleration to the right ($Y_{right}$) are simultaneously in action, this variable was drawn as the optimal factor variable of the classification of drivers who had caused an accident, and the prediction model by discriminant analysis classified drivers who had caused an accident at a rate up to 62.8%, and the prediction model by logistic regression analysis could classify those who had caused an accident at a rate up to 76.7%. In addition, as a result of the verification of model predictive power of the models showed an accuracy rate of 84.1%.

• Journal of the Ergonomics Society of Korea
• /
• v.5 no.2
• /
• pp.27-31
• /
• 1986

There has been a growing interest in the application of biorhythm theory to programmes of accident prevention and performance prediction. In order for biorhythm to be applie to practice its validity and reliability should be established. This paper reported the results of three different set of data, and these data were tabulated and analysed in various ways. The basic method of analysis consisted of stat- istical comparision of actual frequences of occurrence from the collected data with those frequencies which would be expected if biorhythm had no effect. The results of the occurrence data indicated that no definite evidence in support of the influence of the fundamentals could be detected. Actual frequencies of occurrence from the collected data were not significantly different them those expected assuming random occurrence.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.1
• /
• pp.16-24
• /
• 2023

Accidents are greatly reduced through projects to improve frequent traffic accidents. These results show that safety facilities play a big role. Traffic accidents are caused by various causes and various environmental factors, and it is difficult to achieve improvement effects by installing one safety facility or facilities without standards. Therefore, this study analyzed the improvement effect of each accident type by combining the two safety facilities, and suggested a method of predicting the combination of safety facilities suitable for a specific point, including environmental factors such as road type, road type, and traffic. The prediction was carried out by selecting an XGBoost technique that creates one strong prediction model by combining prediction models that can be simple classification. Through this, safety facilities that have had positive effects through improvement projects and safety facilities to be installed at points in need of improvement were derived, and safety facilities effect analysis and prediction methods for future installation points were presented.

• The Journal of Korean Society for School & Community Health Education
• /
• v.13 no.2
• /
• pp.107-118
• /
• 2012

Backgrounds: In order to prevent dental injuries that often occur in child and adolescent, it is intended to investigate and assess actual state of the injury development, present epidemiological background, and consider and discuss for preparing preventive means against the injury development. Purpose: It was attempted to understand major features of dental injuries developing in child and adolescent and indentify high risk factors of dental injuries in child and adolescent. Methods: In this study, 523 cases of computerized data collected as disease entities of dental injuries among 1-18 years old patient visiting S university hospital located in Seoul in 2009 were analyzed and following results were obtained. Results: It was found that the ratio of dental injuries by genders in child and adolescent was 66.14% of male and 33.86% of female. It was shown also that causes of dental injuries by ages were more in order of falling, bumping, chewing, traffic accident, sports, violence, and crash. In addition places where dental injuries occur by ages were home in less than 5 year old group, park, playground, and play yard in 6-11 year old group, park, playground, and play yard also in 12-14 year old group, and stairs, road, and outdoor places such as mountain climbing, beach, and camping in 15-18 year old group. It was found that time rages when dental injuries in child and adolescent often develop were 15-19 o'clock for falling, 15-19 o'clock for crash, 15-19 o'clock for bumping, 19-03 o'clock for violence, 15-19 o'clock for traffic accident, 15-19 o'clock for sports activity, and 15-19 o'clock for chewing. Conclusion: Background of dental injury inducing factors are very complicated and diversified, so deep study and analysis are required for its prediction. Therefore, it seems necessary to identify risk factors by phases such as before, at, and after accident, establish strategies to reduce injury development, and develop and utilize necessary programs.

• Journal of the Korean Society of Safety
• /
• v.25 no.2
• /
• pp.84-88
• /
• 2010

The main point of this study is to find ways to prevent accidents at complex linear sections in advance by improving geometric structure elements that can be considered from the designing stage. Complex linear roads are consisted of sections where straight sections connect with curved sections or sections where curved sections connect with curved sections with relatively high possibility of accidents and accidents can be reduced through improving designing elements in these sections. Therefore, this study aims to develop accident forecasting model in complex linear roads and to clarify major elements affecting traffic accidents. The results of analysis showed that the groups are divided into a group less than 355m based on curve radius of 355m, a group whose curve radius exceeds 355m and a group whose incline exceeds -0.79 and a group whose curve radius is below 355m and incline exceeds -0.79 for straight section + curved section, and for curved section + curved section, it is divided into a group whose first curved section is less than 410m based on curve radius of 410m and the first curve is turning right and a group exceeding 410m and the first curve is turning left. The major variables common in 2 models are front curve radius and curve types(left, right), road surfaces, weather.

• Journal of Korea Society of Industrial Information Systems
• /
• v.28 no.6
• /
• pp.11-20
• /
• 2023

The cost of medical treatment for motor vehicle accidents is increasing every year. In this study, we created a model to predict long-term hospitalization(more than 18 days) among minor patients, which is the main item of increasing traffic accident medical expenses, using five algorithms such as decision tree, and analyzed the factors affecting long-term hospitalization. As a result, the accuracy of the prediction models ranged from 91.377 to 91.451, and there was no significant difference between each model, but the random forest and XGBoost models had the highest accuracy of 91.451. There were significant differences between models in the importance of explanatory variables, such as hospital location, name of disease, and type of hospital, between the long-stay and non-long-stay groups. Model validation was tested by comparing the average accuracy of each model cross-validated(10 times) on the training data with the accuracy of the validation data. To test of the explanatory variables, the chi-square test was used for categorical variables.